July 29, 2011 | 3
When ecosystems are sick, who prescribes the cure? Its not as straight-forward as it is in medicine. A doctor diagnoses a problem and prescribes some medication or treatments to ease the pain or kill infectious agents. Sometimes we battle the insurance agents over the necessity of treatments. This is simplified of course.
In applied ecology, prescribing a cure for conservation problems is not so simple. Not all the “doctors” agree there is a problem. Even when there is agreement, it’s not clear what treatments should be applied. But nearly all the practitioners agree that while there is no cure for conservation problems, there are treatments that alleviate some of the ‘pain’.
How scientists come to a diagnosis is not always straight-forward. Every researcher has a favorite habitat, a favorite species, or a favorite location which they like to work. Not all consider an entire ecosystem or, sometimes, an entire species’ range. There are often good reasons for this, it isn’t borne out of laziness or ignorance. We just can’t sample everything, else it would all be destroyed! Also, many animals are on the run and hard to track, while many plants are hidden among the scenery. Omniscience is, for obvious reasons, lacking in research.
To understand what is needed to conserve we need to first get a handle on how individuals of a species interact with one another. Researchers use a powerful approach called population genetics to understand how plant and animal movements connect various populations around the species range. Species are subdivided into discrete units called populations. The definition of a population is exactly what is trying to be defined in a conservation study. It is not as easy as one might think either!
For instance, how would you define populations among humans? There are societal factors, national boundaries, ethnic groups that broadly reach beyond countries’ borders, etc. Groups or families of humans move around quite a bit and intermarry and mix from abroad and across societal, economic and international boundaries. My own spouse migrated from Sweden and we have since moved all around the North American continent. Our offspring, while born in Pennsylvania will have moved around with us for some time, displacing them from their natal population. Hence, our migratory ecology is extremely complicated and why human population geneticists must often delve deep into our genomes to find useful markers to trace our past migration.
Most plants and animals are better behaved though and restrict themselves to a nice, cozy habitat where their niche is well-defined. And, while recent movement patterns are difficult to make sense of, researchers can get a good grasp on past population behavior using a variety of genetic tools. Analyzing fragments of conserved gene sequences can give us a deeper picture of how populations were historically connected and a more conservative definition of populations. Additionally, other short sections contain patterns of repetitive DNA that are more susceptible to replication errors and are immediately heritable among offspring. These markers, called microsatellites, help us track more recent movements and characterize smaller scales of structure within populations.
Tracking what is happening at the population level in fundamental to many evolutionary biologists. One way that evolution can begin is subdivision with migration ceasing among populations. As they move apart they are only exchanging genes within the subdivision. While often with bad connotations, inbreeding isn’t inherently a bad thing and doesn’t mean that close relatives are necessarily mating with each each other. The amount of inbreeding can be inferred using genetic markers and really show us where a species lies on the evolutionary trajectory.
Imagine a barrier spontaneously arise, perhaps snails on a sheet of ice which breaks apart. The barrier is water which they cannot cross. Those snails can no longer contact one another and their population is now subdivided. Each iceberg is now a subpopulation and those snail present may mate with each other. The microsatellites are heritable and so all those microsatellite combinations present in the subpopulation will be the only ones present. New microsatellites can only arise by mutation of the DNA, which is a random process. Because any particular novel microsatellite could arise independently in any number of populations, researchers use an array of independent genetic markers to gain enough statistical power to detect these convergent occurrences.
Over time though, new microsatellites will eventually arise and it is the over all pattern of shared and unique genotypes (uniques genetic signatures) among populations and subpopulations that shed a light on species’ movements and history. Because researchers can rule out convergent evolution using an array of genetic markers, we know that signatures shared among two or more populations must be the result of migration. Snails from one island must have found a way during their life history to make to another island, mate and integrate its genes into the locals.
One view of an organism is that they are merely proxies, or vectors, for the genes they carry. I think this view is borne out because we study their movements and history using these miniscule snippets of DNA. But the organism itself is a totality: the behavior, the genes, the life history quirks, the mating strategy, you name it. Studying genetics, one can get lost in the world where four letters reign supreme and branches and nodes are the lingua franca in a kingdom of strange analyses. Nevertheless, measuring the flow of genes among populations remains a powerful inferential tool in ecology.
Like a model of manifest destiny, individuals tend to move away from a central population and colonize the fringes, slowly expanding the empire’s reach. New genetic signatures are more likely to be detected at the fringes because the central population is larger and are more freely mating with each other, tending to favor the most common or most advantageous genotypes. While it is poetic to think of genes as flowing among populations, ebbing and flowing from the source to the fringes, there are all types factors that influence gene flow in often unpredictable ways. Some are environmental and outside the control of species, but many are specific biological adaptations, life history traits or behavioral cues. Because species are so widely different, each must be approached carefully, resulting in a very nuanced field of conservation biology. The beauty of evolution really packs a sucker punch to those captivated by it!
A very recent paper by Sexton and colleagues discusses how nuanced gene flow can be. The result was elegant, yet has profound implications for how species might be managed over their ranges. The unassuming and ubiquitous Monkeyflower, Mimulus laciniatus, lives in the foothills of California’s iconic Sierras. It exists in a variety microhabitats along ecological gradients where different traits are superior depending on the climatic conditions. Sexton studied several fitness traits (e.g. emergence, phenology – what growth state the plant was in, and fruit mass) in populations of the annual plant that were central, in higher elevations, and compared those to populations at the range edge where the lower elevations result in a warmer, drier microhabitat (dubbed the warm edge by the authors). They also inferred how these fitness traits were affected by gene flow, either from center to edge or among edge populations.
What they found was that gene flow increased reproductive success, not surprising, but it was most pronounced between populations in similar climates. In general, populations living at the warm edge had the highest fitness in the warmer, drier microhabitats. The model of a central population hub seeding fringe populations would actually be maladaptive in the Monkeyflower. This has to do with the important biological characteristics of plant emergence time and phenological stage. Central population, which are at higher elevations, emerge later in the season since the ice pack is around longer. Offspring transplanted from central to edge populations generally had lower fitness as a result.
“Populations inhabiting novel environments, such as at range limits, should be considered collectively for their potential to produce novel, adaptive genetic combinations. In the race to facilitate species tracking of rapidly changing climates, prescriptive gene flow among range limit populations may represent a form of genetic rescue that increases the evolutionary capacity of range limit populations to respond to rapidly changing selective regimes.” – Sexton et al. 2011
While there are strong opinions about the effectiveness of “genetic rescue”, this study really highlights the importance of phenotype to environment matching. We cannot manage species by pretending local adaptation does not exist. Sexton’s study shows very well how beneficial it is to have the right phenotype for the environment. If managers want to optimize establishment and persistence of new populations then it is important to encourage corridors of gene flow among populations with similar climatic conditions.
As we move to mitigate climate change we would do well to keep this lesson in mind. When treating species conservation problems it is not enough to “take two and call me in the morning”. Those prescriptive migrants must come from the right ‘brand’ to be the most effective. A “generic” prescription may not always as effective as Otherwise we may be doing even more harm, sending species into downward spirals toward extirpation.
Behere, G., Tay, W., Russell, D., Heckel, D., Appleton, B., Kranthi, K., & Batterham, P. (2007). Mitochondrial DNA analysis of field populations of Helicoverpa armigera (Lepidoptera: Noctuidae) and of its relationship to H. zea BMC Evolutionary Biology, 7 (1) DOI: 10.1186/1471-2148-7-117
Sexton JP, Strauss SY, & Rice KJ (2011). Gene flow increases fitness at the warm edge of a species’ range. Proceedings of the National Academy of Sciences of the United States of America, 108 (28), 11704-9 PMID: 21709253
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